Integrating Open Innovation into the Core of Federal R&D Strategy

How government conducts and supports research and development (R&D) is evolving. Open Innovation (OI) includes a new set of R&D approaches that change what topics are possible to study, the types of institutions and individuals that can participate, project timelines and formats, perceived boundaries of disciplines, and even patterns of research progression. OI provides the federal R&D enterprise with expanded options to accelerate the pace of discovery and application and to recruit diverse groups to solve R&D needs that intersect multiple traditional disciplines. Systematically integrating OI into federal R&D strategy alongside traditional research will allow government to more nimbly and effectively respond to today’s challenges. I. Open innovation within federal R&D The United States Federal Government has a large role in the domestic scientific enterprise, funding roughly 25% of the country’s R&D (AAAS 2016). R&D “comprises creative work undertaken on a systematic basis to increase the stock of knowledge... and... to devise new applications” (CRS 2017). Since World War II, a primary strategy of the Federal R&D enterprise has been to competitively fund grants and contracts to address research themes or technical needs. This approach of funding R&D through grants and contracts, as well as directly conducting R&D within federal agencies, is hereafter referred to as the “traditional model”. This model has enabled foundational discoveries and advances in transportation, medicine, genomics, energy, defense, space, and computing (Singer 2014). Scientific and technological advances have accelerated the pace of innovation and development cycles and created a contemporary context that enables and necessitates new modes of R&D. Widespread technological proficiency has created an environment in which startups and individuals have unprecedented access to computing power, prototyping capabilities (e.g., 3D printing), shared research laboratories, and communication networks (Sia and Owens 2015). In parallel, R&D has shifted to become more open, distributed, and collaborative (Kogut and Metiu 2001). From this modern R&D ecosystem has risen the paradigm of Open Innovation (OI). OI “is a more distributed, more participatory, more decentralized approach to [problem solving], based on the observed fact that useful knowledge today is widely distributed, and no [organization], no matter how capable or how big, could innovate effectively on its own” (Chesbrough 2011). OI facilitates systematic exploration and integration of input from sources beyond core project participants, both external and internal to an organization (Chesbrough 2003). Journal of Science Policy & Governance POLICY ANALYSIS: INTEGRATING OPEN INNOVATION www.sciencepolicyjournal.org JSPG., Vol. 15, Issue 1, October 2019 In the 2000s, some federal R&D programs expanded to align with this more open innovation ecosystem and began to broadly adopt OI as a means to accelerate research and take on previously intractable problems. With OI came the adoption of new approaches to support fast exploration of ideas, novel connections across disciplines, and increased participation by previously underused and excluded pools of talent. OI by government is in a period of high growth (Gustetic 2017), aided by recent policy (15 USC 3719) and increasingly formalized infrastructure. As a result, federal R&D is evolving in ways that are reshaping science: dramatically shifting the topics studied, types of participants, project formats, and even patterns of research progression. This article explores the use of OI in federal R&D and identifies policy and institutional areas of need to ensure that the federal R&D enterprise can efficiently and effectively take full advantage of OI to solve today’s urgent and complex problems. II. R&D approaches for the 21st century Many different OI approaches are used by the Federal Government (GAO 2016). Here we present a representative selection of approaches illustrating how incentive prizes, accelerators, and crowdsourcing and citizen science operate in practice and the kinds of problems these approaches help government solve.